The allocation of US AID funds

According to Marco Rubio only 12 cents of every dollar spent from USAID went to recipients, the other 88 cents went to NGOs who pocketed the money.

I tried to fact check that with o3:

However you draw the line, before 2017 well over half—and usually more like 75-90 percent—of USAID money was channelled through third-party NGOs, contractors, and multilateral agencies rather than handed straight to the governments or other local actors in the partner country.

I do support PEPFAR and the earlier vaccine programs, but perhaps those estimates have been underreported as of late?  I do understand that not all third party allocations are wasteful, nonetheless something seems badly off here.  Nor were many US AID defenders keen to deal with such estimates when the major debate was going on.

My excellent Conversation with Theodore Schwartz

Here is the audio, video, and transcript.  Here is part of the episode summary:

Tyler and Ted discuss how the training for a neurosurgeon could be shortened, the institutional factors preventing AI from helping more in neurosurgery, how to pick a good neurosurgeon, the physical and mental demands of the job, why so few women are currently in the field, whether the brain presents the ultimate bottleneck to radical life extension, why he thinks free will is an illusion, the success of deep brain stimulation as a treatment for neurological conditions,  the promise of brain-computer interfaces, what studying epilepsy taught him about human behavior, the biggest bottleneck limiting progress in brain surgery, why he thinks Lee Harvey Oswald acted alone, the Ted Schwartz production function, the new company he’s starting, and much more.

And an excerpt:

COWEN: I know what economists are like, so I’d be very worried, no matter what my algorithm was for selecting someone. Say the people who’ve only been doing operations for three years — should there be a governmental warning label on them the way we put one on cigarettes: “dangerous for your health”? If so, how is it they ever learn?

SCHWARTZ: You raise a great point. I’ve thought about this. I talk about this quite a bit. The general public — when they come to see me, for example, I’m at a training hospital, and I practiced most of my career where I was training residents. They’ll come in to see me, and they’ll say, “I want to make sure that you’re doing my operation. I want to make sure that you’re not letting a resident do the operation.” We’ll have that conversation, and I’ll tell them that I’m doing their operation, but that I oversee residents, and I have assistants in the operating room.

But at the same time that they don’t want the resident touching them, in training, we are obliged to produce neurosurgeons who graduate from the residency capable of doing neurosurgery. They want neurosurgeons to graduate fully competent because on day one, you’re out there taking care of people, but yet they don’t want those trainees touching them when they’re training. That’s obviously an impossible task, to not allow a trainee to do anything, and yet the day they graduate, they’re fully competent to practice on their own.

That’s one of the difficulties involved in training someone to do neurosurgery, where we really don’t have good practice facilities where we can have them practice on cadavers — they’re really not the same. Or have models that they can use — they’re really not the same, or simulations just are not quite as good. At this point, we don’t label physicians as early in their training.

I think if you do a little bit of research when you see your surgeon, there’s a CV there. It’ll say, this is when he graduated, or she graduated from medical school. You can do the calculation on your own and say, “Wow, they just graduated from their training two years ago. Maybe I want someone who has five years under their belt or ten years under their belt.” It’s not that hard to find that information.

COWEN: How do you manage all the standing?

And:

COWEN: Putting yourself aside, do you think you’re a happy group of people overall? How would you assess that?

SCHWARTZ: I think we’re as happy as our last operation went, honestly. Yes, if you go to a neurosurgery meeting, people have smiles on their faces, and they’re going out and shaking hands and telling funny stories and enjoying each other’s company. It is a way that we deal with the enormous pressure that we face.

Not all surgeons are happy-go-lucky. Some are very cold and mechanical in their personalities, and that can be an advantage, to be emotionally isolated from what you’re doing so that you can perform at a high level and not think about the significance of what you’re doing, but just think about the task that you’re doing.

On the whole, yes, we’re happy, but the minute you have a complication or a problem, you become very unhappy, and it weighs on you tremendously. It’s something that we deal with and think about all the time. The complications we have, the patients that we’ve unfortunately hurt and not helped — although they’re few and far between, if you’re a busy neurosurgeon doing complex neurosurgery, that will happen one or two times a year, and you carry those patients with you constantly.

Fun and interesting throughout, definitely recommended.  And I will again recommend Schwartz’s book Gray Matters: A Biography of Brain Surgery.

China divination of the day

The AI-Spiritual-Commerce loop went viral. “DeepSeek Occult Commands” became an online hit. On WeChat, a flood of mini-programs appeared—“AI Face Reading,” “AI Bazi Calculator”—reaching the daily user numbers of medium e-commerce apps. A 9.9-yuan facial reading could be resold again and again through referral links, with some users earning over 30,000 yuan a month. DeepSeek hit 20 million daily active users in just 20 days. At one point, its servers crashed from too many people requesting horoscopes.

On social media, commands like “Full Bazi Chart Breakdown” and “Zi Wei Dou Shu Love Match” turned into memes. One user running a fortune-telling template got over 1,000 private messages in ten days. The AI could write entire reports on personality, karma, and even create fake palm readings about “past life experiences.” People lined up online at 1:00 a.m. to “get their fate explained.”

Meanwhile, a competing AI company, Kimi, released a tarot bot—immediately the platform’s most used tool. Others followed: Quin, Vedic, Lumi, Tarotmaster, SigniFi—each more strange than the last. The result? A tech-driven blow to the market for real human tarot readers.

In this strange mix, AI—the symbol of modern thinking—has been used to automate some of the least logical parts of human behavior. Users don’t care how the systems work. They just want a clean, digital prophecy. The same technology that should help us face reality is now mass-producing fantasy—on a huge scale.

Here is the full story.  Via the always excellent The Browser.

Changes in the College Mobility Pipeline Since 1900

By Zachary Bleemer and Sarah Quincy:

Going to college has consistently conferred a large wage premium. We show that the relative premium received by lower-income Americans has halved since 1960. We decompose this steady rise in ‘collegiate regressivity’ using dozens of survey and administrative datasets documenting 1900–2020 wage premiums and the composition and value-added of collegiate institutions and majors. Three factors explain 80 percent of collegiate regressivity’s growth. First, the teaching-oriented public universities where lower-income students are concentrated have relatively declined in funding, retention, and economic value since 1960. Second, lower-income students have been disproportionately diverted into community and for-profit colleges since 1980 and 1990, respectively. Third, higher-income students’ falling humanities enrollment and rising computer science enrollment since 2000 have increased their degrees’ value. Selection into college-going and across four-year universities are second-order. College-going provided equitable returns before 1960, but collegiate regressivity now curtails higher education’s potential to reduce inequality and mediates 25 percent of intergenerational income transmission.

An additional hypothesis is that these days the American population is “more sorted.”  We no longer have the same number of geniuses going to New York city colleges, for instance.  Here is the full NBER paper.

What I’ve been reading

1. Eric Ambler, Cause for Alarm.  Are all his books so good?  So far yes.  With very simple means he redefines what it means to be a good writer of thrillers.  Very English, written and set in Italy 1937, with a foolish Englishman who could be out of a Hitchcock movie.  They still called it Laibach back then, the menace of the pending war casts the proper shadow over the whole novel.

2. Futurism & Europe: The Aesthetics of a New World, Fabio Benzi and various editors.  “By their aesthetics ye shall know them!”  What were the aesthetics of the futurist movement in the early 20th century?  Should we approve of those aesthetics?  This book is a good starting point for asking that question.  Nice color plates.

3. Philip Shenon, Jesus Wept: Seven Popes and the Battle for the Soul of the Catholic Church.  A very well-written and useful book, I cannot say I have a stance on the issues per se.  It is one of my defects that I cannot care enough about the politics of the Catholic Church — I feel there are already too many separate countries with their own politics.  Nor do I feel close to either “the liberals” or “the conservatives” in this debate.  I do think the current American Pope — who seems “pilled” on many things — will be a big deal, I suspect mostly for the better.

4. Renaud Camus, Enemy of the Disaster: Selected Political Writings.  Interesting enough, and if you can read the French lefties why not this guy too?  That said, he could be more specific on “the Great Replacement.”  The most likely scenario is a France that is about twenty percent Muslim, wracked with periodic ethnic issues, but doing more or less OK.  In any case you should not be afraid to read this book, even though for a while it was considered cancel-worthy.

5. Tom Arnold-Foster, Walter Lippmann: An Intellectual Biography.  With so many forms of liberalism in semi-collapse, Lippmann is suddenly relevant again.  He had faith in experts, and also was not crazy.  But somehow is not deep enough to hold my interest?  Still, this book is very well done.

I will not soon have time to get to Joseph Torigian, The Party’s Interests Come First: The Life of Xi Zhongxun, Father of Xi Jinping, but it looks excellent.

The economics of sleep

Full-time, prime-age male workers in the top income quartile sleep around half an hour less per day than those in the lowest quartile.

At the macro level, average sleep duration decreases as a country’s GDP increases.

Higher-income individuals allocate more time to other leisure activities, such as social outings and internet usage, substituting sleep.

Here is the paper by Cristián Jara, Francisca Pérez, and Rodrigo Wagner. Via the excellent Kevin Lewis.

Politically correct LLMs

Despite identical professional qualifications across genders, all LLMs consistently favored female-named candidates when selecting the most qualified candidate for the job. Female candidates were selected in 56.9% of cases, compared to 43.1% for male candidates (two-proportion z-test = 33.99, p < 10⁻252 ). The observed effect size was small to medium (Cohen’s h = 0.28; odds=1.32, 95% CI [1.29, 1.35]). In the figures below, asterisks (*) indicate statistically significant results (p < 0.05) from two-proportion z-tests conducted on each individual model, with significance levels adjusted for multiple comparisons using the Benjamin-Hochberg False Discovery Rate correction…

In a further experiment, it was noted that the inclusion of gender concordant preferred pronouns (e.g., he/him, she/her) next to candidates’ names increased the likelihood of the models selecting that candidate, both for males and females, although females were still preferred overall. Candidates with listed pronouns were chosen 53.0% of the time, compared to 47.0% for those without (proportion z-test = 14.75, p < 10⁻48; Cohen’s h = 0.12; odds=1.13, 95% CI [1.10, 1.15]). Out of 22 LLMs, 17 reached individually statistically significant preferences (FDR corrected) for selecting the candidates with preferred pronouns appended to their names.

Here is more by David Rozado.  So there is still some alignment work to do here?  Or does this reflect the alignment work already?

Fast Grants it ain’t

In an interview with German business newspaper Handelsblatt, Calviño has emphasized a newfound willingness to embrace risk within the EIB’s financing strategies. The bank aims to process startup financing applications within six months, significantly improving from the current 18-month timespan. Calviño describes this accelerated timeline as a ‘gamechanger,’ pointing out that the high-paced nature of tech innovation requires nimble response times to keep up with market dynamics.

Here is the full document, I believe the European Investment Bank is (by far) the largest VC in Europe proper.

Monday assorted links

1. “Your Fingers Wrinkle in the Same Pattern Every Time After Long Exposure to Water.

2. “Romania’s next president was 1st in the world in the International Maths Olympiad 2 years in a row with maximum score…

3. Monkey markets in everything, short video.

4. Some Miami schools are embracing AI (NYT).

5. Arpit Gupta delivers an “ouch” to the trade-skeptical left.

6. Lamorna Ash, Don’t Forget We’re Here Forever: A New Generation’s Search for Religion, coming out in July.

7. What is the correlation between education and church attendance, in both America and Europe?

8. Who says AI isn’t useful?: “…we conducted an extensive ChatGPT query to develop a concise AI-generated information sheet designed to coach students in feigning ADHD during a clinical assessment”

Partisan Corporate Speech

We construct a novel measure of partisan corporate speech using natural language processing techniques and use it to establish three stylized facts. First, the volume of partisan corporate speech has risen sharply between 2012 and 2022. Second, this increase has been disproportionately driven by companies adopting more Democratic-leaning language, a trend that is widespread across industries, geographies, and CEO political affiliations. Third, partisan corporate statements are followed by negative abnormal stock returns, with significant heterogeneity by shareholders’ degree of alignment with the statement. Finally, we propose a theoretical framework and provide suggestive empirical evidence that these trends are at least in part driven by a shift in investors’ nonpecuniary preferences with respect to partisan corporate speech.

That is from a recent paper by William Cassidy and Elisabeth Kempf.  Via the excellent Kevin Lewis.